An intrusion detection system (IDS) is key to having a comprehensive cybersecurity solution against any attack, and artificial intelligence techniques have been combined with all the features of the IoT to improve security. In response to this, in this research, an IDS technique driven by a modified random forest algorithm has been formulated to improve the system for IoT. To this end, the target is made as one-hot encoding, bootstrapping with less redundancy, adding a hybrid features selection method into the random forest algorithm, and modifying the ranking stage in the random forest algorithm. Furthermore, three datasets have been used in this research, IoTID20, UNSW-NB15, and IoT-23. The results are compared with the three datasets men

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the

Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

Abstract In this study, an investigation is conducted to realise the possibility of organic materials use in radio frequency (RF) electronics for RF-energy harvesting. Iraqi palm tree remnants mixed with nickel oxide nanoparticles hosted in polyethylene, INP substrates, is proposed for this study. Moreover, a metamaterial (MTM) antenna is printed on the created INP substrate of 0.8 mm thickness using silver nanoparticles conductive ink. The fabricated antenna performances are instigated numerically than validated experimentally in terms of S11 spectra and radiation patterns. It is found that the proposed antenna shows an ultra-wide band matching bandwidth to cover the frequencies from 2.4 to 10 GHz with bore-sight gain variation from 2.2 to

Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

Dual-species biofilms of Pseudomonas aeruginosa and Staphylococcus aureus generate difficult-to-treat illnesses. Nutrition stress in biofilms affects physiology, microbial metabolism, and species interactions, impacting bacteria growth and survival. Furthermore, the function of alginate, which is encoded by the algD gene, in the production of biofilms has been established. The present study aimed at investigating the impact of starvation on algD gene expression in single-species biofilm of P. aeruginosa and dual-species biofilms of P. aeruginosa and S. aureus from hospital sewage. A total of six P. aeruginosa and six S. aureus isolates were obtained from the microbiology laboratory at the Department of Biology, College of Science, Universit

Background: An injury to both the primary and permanent teeth and the supporting structures is one of the most common dental problems seen in children. Splinting is usually difficult or impossible to perform in the primary dentition (due to diminutive room size and lack of patient cooperation). Healing must, therefore, occur despite mobility at the fracture line, usually resulting in interposition of connective tissue. In some instances, infection will occur in the coronal pulp. The present study reported a case of trauma to the anterior primary teeth and alveolar bone in a four year old child. The trauma has caused fracture to the crowns and roots of the primary anterior teeth. The following case was managed in a procedure that may prov

Background: An injury to both the primary and permanent teeth and the supporting structures is one of the most common dental problems seen in children. Splinting is usually difficult or impossible to perform in the primary dentition (due to diminutive room size and lack of patient cooperation). Healing must, therefore, occur despite mobility at the fracture line, usually resulting in interposition of connective tissue. In some instances, infection will occur in the coronal pulp. The present study reported a case of trauma to the anterior primary teeth and alveolar bone in a four year old child. The trauma has caused fracture to the crowns and roots of the primary anterior teeth. The following case was managed in a procedure that may